bert-finetuned-ner-chemreact

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: chem-bert-cased
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# chem-bert-cased
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7331
+- Precision: 0.4357
+- Recall: 0.5028
+- F1: 0.4668
+- Accuracy: 0.7661
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 51   | 0.9568          | 0.3458    | 0.0882 | 0.1405 | 0.7141   |
+| No log        | 2.0   | 102  | 0.8359          | 0.3301    | 0.2693 | 0.2966 | 0.7363   |
+| No log        | 3.0   | 153  | 0.7562          | 0.3932    | 0.4678 | 0.4273 | 0.7548   |
+| No log        | 4.0   | 204  | 0.7406          | 0.4269    | 0.4059 | 0.4161 | 0.7623   |
+| No log        | 5.0   | 255  | 0.7331          | 0.4357    | 0.5028 | 0.4668 | 0.7661   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1